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backend: fix buffer overrun in repeat penalty code
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Caught with AddressSanitizer running a basic prompt test against llmodel
standalone. This fix allows ASan builds to complete a simple prompt
without illegal accesses but there are still notably several leaks.
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apage43 authored and manyoso committed May 17, 2023
1 parent 26cb31c commit e6fd0a2
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Showing 3 changed files with 9 additions and 6 deletions.
5 changes: 3 additions & 2 deletions gpt4all-backend/gptj.cpp
Original file line number Diff line number Diff line change
Expand Up @@ -993,9 +993,10 @@ void GPTJ::prompt(const std::string &prompt,
gpt_vocab::id id = 0;
{
const int64_t t_start_sample_us = ggml_time_us();
const size_t n_prev_toks = std::min((size_t) promptCtx.repeat_last_n, promptCtx.tokens.size());
id = gpt_sample_top_k_top_p(d_ptr->vocab, n_vocab,
promptCtx.tokens.data() + promptCtx.n_ctx - promptCtx.n_ctx,
promptCtx.n_ctx,
promptCtx.tokens.data() + promptCtx.tokens.size() - n_prev_toks,
n_prev_toks,
promptCtx.logits,
promptCtx.top_k, promptCtx.top_p, promptCtx.temp,
promptCtx.repeat_penalty,
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5 changes: 3 additions & 2 deletions gpt4all-backend/llamamodel.cpp
Original file line number Diff line number Diff line change
Expand Up @@ -180,9 +180,10 @@ void LLamaModel::prompt(const std::string &prompt,
int32_t totalPredictions = 0;
for (int i = 0; i < promptCtx.n_predict; i++) {
// sample next token
const size_t n_prev_toks = std::min((size_t) promptCtx.repeat_last_n, promptCtx.tokens.size());
llama_token id = llama_sample_top_p_top_k(d_ptr->ctx,
promptCtx.tokens.data() + promptCtx.n_ctx - promptCtx.repeat_last_n,
promptCtx.repeat_last_n, promptCtx.top_k, promptCtx.top_p, promptCtx.temp,
promptCtx.tokens.data() + promptCtx.tokens.size() - n_prev_toks,
n_prev_toks, promptCtx.top_k, promptCtx.top_p, promptCtx.temp,
promptCtx.repeat_penalty);

// Check if the context has run out...
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5 changes: 3 additions & 2 deletions gpt4all-backend/mpt.cpp
Original file line number Diff line number Diff line change
Expand Up @@ -918,9 +918,10 @@ void MPT::prompt(const std::string &prompt,
int id = 0;
{
const int64_t t_start_sample_us = ggml_time_us();
const size_t n_prev_toks = std::min((size_t) promptCtx.repeat_last_n, promptCtx.tokens.size());
id = gpt_sample_top_k_top_p(d_ptr->vocab, n_vocab,
promptCtx.tokens.data() + promptCtx.n_ctx - promptCtx.n_ctx,
promptCtx.n_ctx,
promptCtx.tokens.data() + promptCtx.tokens.size() - n_prev_toks,
n_prev_toks,
promptCtx.logits,
promptCtx.top_k, promptCtx.top_p, promptCtx.temp,
promptCtx.repeat_penalty,
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